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ropensci · Jul 31, 2024 · 3ef4ac4 · 3ef4ac4
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Showing 6 changed files with 7 additions and 17 deletions.
diff --git a/R/dl.R b/R/dl.R
@@ -89,7 +89,7 @@ dl_stats19 = function(year = NULL,
       message("Data already exists in data_dir, not downloading")
     }
   } else {
-    if (interactive() & !many_found) {
+    if (interactive() && !many_found) {
       if (ask) {
         resp = readline(phrase())
       } else {

diff --git a/R/format.R b/R/format.R
@@ -86,7 +86,7 @@ format_stats19 = function(x, type) {
     # See https://github.com/ropensci/stats19/issues/235#issuecomment-2254257770
     matched_labels = lookup$label[match(x[[i]], lookup$code)]
     x[[i]] = ifelse(is.na(matched_labels), x[[i]], matched_labels)
-    x[[i]] = as(x[[i]], original_class)
+    x[[i]] = methods::as(x[[i]], original_class)
   }
 
   date_in_names = "date" %in% names(x)

diff --git a/R/read.R b/R/read.R
@@ -185,8 +185,6 @@ convert_to_col_type = function(type) {
          readr::col_guess())
 }
 
-data("stats19_variables", package = "stats19")
-
 # Create a named list of column types
 unique_vars = unique(stats19_variables$variable)
 unique_types = sapply(unique_vars, function(v) {

diff --git a/data-raw/tests/test-format_vehicle_issue_235.qmd b/data-raw/tests/test-format_vehicle_issue_235.qmd
@@ -43,4 +43,5 @@ table(cas$age_of_casualty)
 #   8822   7197   5769   3722   2695   1908   1342    885    546    351    333 
 #     99    100    101    102    103    104 
 #   3356     13      7      4      1      1 
-```
+```
+
diff --git a/vignettes/blog.Rmd b/vignettes/blog.Rmd
@@ -109,15 +109,7 @@ There is a schema covering these tables but a good amount of work is needed to u
 
 The annual statistics have not been released in a consistent way either, making it hard for people to download, or even find, the relevant files.
 For example, there are separate files for each of the above tables for certain years (e.g. 2016, 2022) but not for all of 1979 - 2022 or 2018 now.
-The largest chunk is the 1979 - 2004 data, which is made available in a huge ZIP file ([link](https://data.dft.gov.uk/road-accidents-safety-data/Stats19-Data1979-2004.zip)).
-Unzipped this contains the following 3 files, which occupy almost 2 GB on your hard drive: 
-
-```sh
-721M Apr  3  2013 Accidents7904.csv
-344M Apr  3  2013 Casualty7904.csv
-688M Apr  3  2013 Vehicles7904.csv
-# total 1.753 GB data
-```
+The largest chunk contains data from 1979.
 
 #### Note
 

diff --git a/vignettes/stats19.Rmd b/vignettes/stats19.Rmd
@@ -23,7 +23,7 @@ knitr::opts_chunk$set(
 ## Introduction
 
 **stats19** enables access to and processing of Great Britain's official road traffic casualty database, [STATS19](https://www.data.gov.uk/dataset/cb7ae6f0-4be6-4935-9277-47e5ce24a11f/road-safety-data). 
-A description of variables in the database can be found in a [document](https://data.dft.gov.uk/road-accidents-safety-data/Brief-guide-to%20road-accidents-and-safety-data.doc) provided by the UK's Department for Transport (DfT).
+A description of variables in the database can be found in a [guidance](https://www.gov.uk/guidance/road-accident-and-safety-statistics-guidance) provided by the UK's Department for Transport (DfT).
 The datasets are collectively called STATS19 after the form used to report them, which can be found [here](https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/995422/stats19.pdf).
 This vignette focuses on how to use the **stats19** package to work with STATS19 data.
 
@@ -177,7 +177,7 @@ columns (variables) for
 129,982 crashes.
 
 This work was done by `read_collisions(format = FALSE)`, which imported the "raw" STATS19 data without cleaning messy column names or re-categorising the outputs.
-`format_collisions()` function automates the process of matching column names with variable names and labels in a [`.xls` file](https://data.dft.gov.uk/road-accidents-safety-data/variable%20lookup.xls) provided by the DfT.
+`format_collisions()` function automates the process of matching column names with variable names provided by the DfT.
 This means `crashes_2022` is much more usable than `crashes_2022_raw`, as shown below, which shows some key variables in the messy and clean datasets:
 
 ```{r crashes2022-columns}
@@ -204,7 +204,6 @@ crashes_2022[random_n, key_vars]
 ## Format STATS19 data
 
 It is also possible to import the "raw" data as provided by the DfT.
-A [`.xls` file](https://data.dft.gov.uk/road-accidents-safety-data/variable%20lookup.xls) provided by the DfT defines the column names for the datasets provided.
 The packaged datasets `stats19_variables` and `stats19_schema` provide summary information about the contents of this data guide.
 These contain the full variable names in the guide (`stats19_variables`) and a complete look up table relating integer values to the `.csv` files provided by the DfT and their labels (`stats19_schema`).
 The first rows of each dataset are shown below: